Google Inc.

Synopsys, Inc.

Jinan Lou

Jie Yang

Maureen Heymans

Luis Garcia Pueyo

Hui Tan

Vanja Josifovski

Mike Bendersky

MyLinh Yang

Amitabh Saikia

Marc-Allen Cartright

Andre Rohe

Yonatan Zunger

Sangsoo Sung

Matthew E Kulick

Daniel Belov

Kayhan Kucukcakar

Lucian Florin Cionca

Jing Chyuarn Lin

Xincheng Zhang

Anandsudhakar Kesari

James Bradley Wendt

Yifeng Lu

Jing Xie

Zhiyu Wang

Sumitro Samaddar

Ying Sheng

Harish Rajamani

Mohit Oberoi

Techniques are described herein for automatically generating data extraction templates for structured documents (e.g., B2C emails, invoices, bills, invitations, etc.), and for assigning classifications to those data extraction templates to streamline data extraction from subsequent structured documents. In various implementations, a data extraction template generated from a cluster of structured documents that share fixed content may be identified. Features of the cluster of structured documents may be applied as input to extraction machine learning model(s) trained to provide location(s) of transient field(s) in structured documents, to determine location(s) of transient field(s) in the cluster of structured documents. An association between the data extraction template and the determined transient field location(s) may be stored. Based on the association, data point(s) may be extracted from a given structured document of a user that shares fixed content with the cluster of structured documents. The extracted data point(s) may be surfaced to the user.

Template-based structured document classification and extraction

Techniques are described herein for generating and applying event data extraction templates. In various implementations, a data extraction template may be applied to structured communications to extract, from each structured communication, event data associated with a transient markup language path indicated in the data extraction template. The data extraction template may include an event-related semantic data type assigned to the transient markup language path and a strength of association between the transient structural path and the event-related semantic data type. Feedback may be obtained concerning event data extracted from one or more of the structured communications. Based on the feedback, the strength of association between the transient markup language path and the event-related semantic data type may be altered. The data extraction template may then be applied to a subsequent structured communication to extract new event data from the structured communication based on the altered strength of association.

Generating and applying event data extraction templates

Methods and apparatus related to clustering documents based on one or more classification terms and optionally based on similarity of structural paths of the documents. In some implementations, the documents are communications such as structured emails or other structured communications. In some of those implementations, clustering the communications includes identifying a plurality of classification terms indicative of a classification, identifying a corpus of communications that includes communications that are not labeled with an association to the classification, and determining a cluster of the communications based on occurrence of one or more of the classification terms in the communications of the cluster.

Clustering communications based on classification

Methods and apparatus are described herein for generating and applying event data extraction templates. In various implementations, a set of structural paths may be identified from a corpus of communications. A first structural path of the set of structural paths, associated with a first segment of text, may be classified as transient in response to a determination that a frequency of occurrences of the first segment of text across the corpus satisfies a criterion. Event heuristics may be applied to the communications of the corpus. A determination may be made, based on the applying, that the communications of the corpus are event-related. An event data type may be assigned to the transient structural path based on the applying. An event data extraction template may be generated to extract, from one or more subsequent communications, one or more event-related segments of text associated with the transient structural path.

In one aspect, a method includes receiving an indication of a request from a user to view a stream associated with the user, generating a request for one or more items visible to the user for display within the stream, the request including a search query identifying search criteria including one or more tokens, the one or more tokens including at least a user token identifying the user, receiving one or more items in response to the request, the one or more items including at least one of the one or more tokens and further being visible to the user and providing the one or more items for display to the user within the stream in response to the request. Other aspects can be embodied in corresponding systems and apparatus, including computer program products.

Query-based stream

Techniques for using social networking information may include making a determination that content authored by a first party references a second party more than a specified number of times. An adjustment in affinity may be made between the first party and the second party in the social network in response to the determination. Making the adjustment in affinity may include modifying a social graph of at least the first party that is referenced by the social network in order to reflect the adjustment in affinity. Modifying the social graph includes creating a closer connection between the first party and the second party than had existed prior to the determination. In response to the adjustment in the affinity, promotion is adjusted, to the first party, of content in the social network that has a connection to the second party.

Using social networking information

A method for reaching signoff closure in an ECO (engineering change order) process involves the use of violation context data from the signoff tool as the basis for design layout modifications in an implementation tool. The violation context data includes violation information other than violation location/path information. Because the signoff tool, and more specifically, the signoff algorithm used by that tool is the most accurate model of actual IC behavior, the use of violation context data generated by the signoff tool to implement changes to the design layout will generally produce appropriate and effective results. By accessing this violation context data from the signoff tool, an implementation tool need not rely on its less accurate implementation analysis to determine the optimal design layout modifications for correcting violations detected by the signoff tool.

Engineering change order process optimization

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Cupertino, CA, United States of America

Jinan Lou